pharmacological approaches to remediate …

PHARMACOLOGICAL APPROACHES TO REMEDIATE NEUROCOGNITIVE

IMPAIRMENT IN COCAINE-DEPENDENT INDIVIDUALS

A Dissertation Presented to the

Faculty of the College of Education

University of Houston

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Philosophy

by

James J. Mahoney, III

May 2014



A Dissertation for the Degree


by


Approved by Dissertation Committee:

________________________________

Dr. Tam K. Dao, Chairperson

___________________________________________

Dr. Susan X Day, Committee Member

________________________________________

Dr. Norma Olvera, Committee Member

________________________________________

Dr. Richard De La Garza, II, Committee Member

________________________________________

Dr. Robert H. McPherson, Dean

College of Education

May 2014



An Abstract

of a Dissertation Presented to the

Faculty of the College of Education

University of Houston

In Partial Fulfillment

of the Requirements for the Degree


by


May 2014

Mahoney, III, James J. Pharmacological Approaches to Remediate Neurocognitive

Impairment in Cocaine-Dependent Individuals

Abstract

The goal of this study was to determine whether demographic (e.g. ethnicity, gender,

etc.), drug use (e.g. years of cocaine use, days cocaine used in the past 30, comorbid

substance use, etc.), or mood (BDI-II, LSC-R, and ASI-Lite scores) variables affected

neurocognitive functioning in cocaine-dependent participants. In addition, two candidate

medications were evaluated to assess whether they have the potential to improve

neurocognitive functioning in cocaine-dependent individuals. There were two separate

studys as part of this dissertation. Study 1 involved the investigation of demographic and

drug use variables contributing to neurocognitive deficits in 125 cocaine dependent

individuals. Study 2 compared the efficacy of two acetylcholinesterase inhibitors:

rivastigmine and huperzine (as well as a control group randomized to receive placebo) as

potential treatments for cocaine-induced neurocognitive impairment. Twenty-eight

individuals were randomized to receive rivastigmine, 29 were randomized to receive

huperzine, and 15 were randomized to receive placebo. Before study medication

randomization, participants completed a battery of neurocognitive assessments and

completed the same battery of assessments following 8 days of medication/placebo

treatment. One of the factors that detrimentally affects cocaine-dependent individuals as

they seek treatment is the presence of neurocognitive deficits produced or exacerbated by

cocaine use. Since long-term, high-dose cocaine use is a risk factor for the onset of

neurocognitive impairment in humans, it is critical that these deficits be addressed in

order to improve treatment outcomes. Study 1 utilized only baseline data (independent of

any medication treatment) and Study 2 used both pre-treatment (baseline, before

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medication administration) and post-treatment (following medication administration)

data. Pearson product moment correlations and analysis of variance (ANOVA) were

used to evaluate the association between demographic and drug use variables and

performance on the neurocognitive measures. ANOVA was used to evaluate medication

versus placebo effects on test performance pre- and post-treatment. Study 1 revealed that

there were no gender or race differences in neurocognition between groups. Further,

comorbid substance use (e.g. nicotine, alcohol, or marijuana) did not affect

neurocognition. Study 2 showed that treatment with rivastigmine significantly improved

episodic memory, though treatment with huperzine did not affect neurocognition. On the

basis of outcomes from Study 1 and Study 2, we contend that cocaine associated

neurocognitive impairment remains an important target of treatment. Given that cocaine

addiction is associated with widespread functional difficulties, such as unemployment

and relapse to dependence, it is plausible that reversing neurocognitive impairments will

ameliorate these functional difficulties.

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TABLE OF CONTENTS

Chapter Page

I. INTRODUCTION

A. The Problem and Consequences of Cocaine Use ………...…………………………………………...1

II. REVIEW OF RECENT LITERATURE

A. Neurocognitive Deficits in Cocaine-dependent Individuals…………………………...……………...2

B. Research Questions and Hypotheses…………………………………………………………………..9

C. Implications…………………………………………………………………………………………..10

III. METHODOLOGY

A. Procedure - Assessments……………………………………………………………………………...11

B. Procedures - Neurocognitive Battery…………………………………………………………….......14

C. Study 1 – Demographic/drug use variables which may affect neurocognition…………………...…17

(Gender; Race; Smoking Status; Years, Recent, Daily Cocaine Use, etc.)

D. Study 2 – Rivastigmine or Huperzine as a treatment for neurocognitive impairment……………….18

IV. Results

A. Study 1 – Demographic and drug use variables which may affect neurocognition………………….20

B. Study 2 – Rivastigmine or Huperzine as a treatment for neurocognitive impairment……………….34

V. Conclusion and Summary

A. Study 1 – Demographic and drug use variables which may affect neurocognition…………………..40

B. Study 2 – Rivastigmine or Huperzine as a treatment for neurocognitive impairment……………......50

C. Overall Conclusion and Summary……………………………………………………………............52

VI. References………………………………………………………………………………………………..54

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List of Tables

Table Page

1. Demo/Drug Use Statistics and overall Neurocognitive Performance for the entire

sample………………………………………………………………………………..21

2. Neurocognitive Functioning in Males versus Females………………………………23

3. Neurocognitive Functioning in African Americans versus Caucasians……………..25

4. Neurocognitive Functioning in Cigarette Smokers versus Non-Smokers…………...27

5. Neurocognitive Functioning in Alcohol Drinkers versus Non-Drinkers…………….29

6. Neurocognitive Functioning in Marijuana Smokers versus Non-Smokers………….31

7. Correlations between Demographic, Drug Use, and Mood Variables and

Neurocognitive Performance………………………………………………………...33

8. Demo/Drug Use Statistics for Study 2……………………………………………….37

9. Neurocognitive Performance on those Randomized to Rivastigmine versus

Placebo……………………………………………………………………………….38

10. Neurocognitive Performance on those Randomized to Huperzine versus Placebo….39

CHAPTER I

INTRODUCTION

A. THE PROBLEM AND DEFINITION OF COCAINE-DEPENDENCE

Cocaine is one of the most commonly abused psychoactive substances in North

America. Before understanding the consequences and repercussions of cocaine use and

the behavioral manifestations which coincide with cocaine dependence, one must first

understand what cocaine dependence entails. As defined by the Diagnostic and

Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV-TR; American

Psychiatric Association, 2000), cocaine dependence includes a maladaptive pattern of

substance use leading to clinically significant distress, as manifested by three (or more)

of the following, occurring within a 12-month period: 1) tolerance to the cocaine (a need

for more amounts of the cocaine to achieve intoxication or a diminished effect with

continued use of the same amount of the drug); 2) withdrawal from the cocaine

(including taking more cocaine to avoid symptoms of withdrawal); 3) taking more

cocaine in larger amounts or over a longer period than originally intended; 4) a persistent

desire or unsuccessful efforts to cut down on cocaine usage; 5) a great deal of time spent

in activities necessary to obtain the cocaine (contacting and meeting suppliers), using the

cocaine (repeatedly using cocaine) and recovering from the effects produced by cocaine

(during withdrawal); 6) important social, occupational, or recreational activities given up

or reduced because of cocaine use; 7) cocaine use continued despite knowledge of having

a persistent or recurrent physical or psychological problem that is likely to have been

caused or exacerbated by the substance.

CHAPTER II

REVIEW OF RECENT LITERATURE

A. NEUROCOGNITIVE DEFICITS AND COCAINE-DEPENDENCE

One of the factors that impedes on treatment success for cocaine-dependent

individuals is the presence of neurocognitive deficits produced or exacerbated by cocaine

use. Long-term, high-dose cocaine use is a risk factor for the onset of neurocognitive

impairment in humans (e.g. Bolla & Cadet, 2007; Jovanovski, Erb, & Zakzanis, 2005).

Jovanovski (2005) conducted a meta-analytic review (15 studies that included 586

matched controls and 481 abstinent cocaine users), which revealed effect sizes of

moderate or greater magnitude for attention, episodic memory, and working memory,

demonstrating that cocaine-dependent individuals experience dysfunction in these

domains. Specifically, these neurocognitive impairments affect day-to-day functioning;

for example, the presence of cocaine-associated neurocognitive impairment is associated

with poor treatment retention (Aharonovich, Amrhein, Bisaga, Nunes, & Hasin, 2008).

These neurocognitive deficiencies are critical as they affect treatment and cocaine

abstinence. For example, if there are deficits in attention, cocaine-dependent individuals

may be unable to maintain focus, attend, and follow through on treatment plans and goals

provided during the therapy process. In addition, if there are deficits in episodic memory,

these individuals may have a difficult time remembering both the positive and negative

events (including triggers) in their life or specific techniques taught during treatment that

may also impede their progress. Also, if their cocaine use has caused deficits in working

memory, reasoning, and comprehension, then it is possible that information processing

will be affected adversely. Thus, it is important to take all of these factors and

3

neurocognitive deficiencies into consideration when attempting to treat someone with

cocaine-dependence.

It also is important to consider possible drug use and demographic variables that

may play a role in neurocognitive functioning. Previous investigations suggested that, in

nondrug using individuals, gender moderates neurocognition. In one report of healthy

individuals, males performed significantly better than females in spatial and object

versions of the n-back working memory task (Lejbak, Crossley, & Vrbancic, 2011).

Also, males tended to perform slightly better than females on the Iowa Gambling Task, a

measure of decision making and executive functioning (Bechara & Martin, 2004; Bolla,

Eldreth, Matochik, & Cadet, 2004). In addition, males performed significantly better

than females on several visuospatial tests, including mental rotation (Peters, Manning, &

Reimers, 2007), fine motor tasks (Nicholson & Kimura, 1996), and spatial navigation

memory (Rahman, Wilson, & Abrahams, 2003; Voyer, Voyer, & Bryden, 1995).

Conversely, when comparing the performance on tasks focused on verbal memory,

females have performed significantly better than males in verbal recall tasks across

different age groups (Bleecker, Bolla-Wilson, Agnew, & Meyers, 1988). Similarly,

females were significantly better than men on tests of verbal memory, perceptual speed,

and spatial memory for object locations (Herlitz, Nilsson, & Backman, 1997; Rahman et

al., 2003). However, the often cited female advantage in verbal fluency is less clear, with

the advantage apparent on specific semantic items and higher order category fluency (e.g.

Rahman, van Turennout, & Levelt, 2003), but less apparent on letter fluency (Herlitz et

al., 1997).

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While the literature on gender differences and neurocognitive performance in

stimulant dependent individuals is sparse, the topic is of considerable interest considering

the differential effects stimulant use has on male versus female users, especially

considering that the results from published reports are mixed. For example, long-term

cocaine use is associated with more debilitating effects on women (Anker & Carroll,

2011), and this finding may extend to differences in neurocognition. Conversely,

Rahman and Clarke (2005) found that among recreational cocaine users who had been

abstinent for three days, males exhibited poorer attention and more verbal recognition

errors than female users. In addition, in a meta-analytic review by Scott and colleagues

(2007), the primary conclusion was that methamphetamine may differentially affect

cognitive function in males compared to females. In a separate report, it was found that

there were no overall gender differences with regard to neurocognition, specifically in the

domains of verbal learning and memory (Chang et al., 2005). Conversely, Price and

colleagues found that female cocaine users had fine motor impairment, and this may be

attributed to frequency of use in the months prior to testing (Price et al., 2011).

While the role of race variability on the neurocognitive performance of cocaine-

dependent individuals is not well described in the literature, it has been reported that, in

non-drug using, neurologically normal individuals, African Americans tend to perform

more poorly than Caucasians on tests of cognitive functioning (Ford, Haley, Thrower,

West, & Harrell, 1996; Kuller et al., 1998; Manly et al., 1998). The data suggest that

African Americans may be at greater risk to be misdiagnosed with learning disabilities or

general cognitive impairment. There are several possible reasons for this disparity,

including parental influence and early educational experiences. Specifically, African

5

Americans with lower neurocognitive functioning were more likely than their Caucasian

counterparts to have parents who did not graduate from high school and reported having

non-reading related disabilities (Byrd, Walden Miller, Reilly, Weber, Wall, & Heaton,

2006). While race differences regarding neurocognition have been noted in healthy

controls, there have not yet been any published studies investigating this factor in

cocaine-dependent individuals.

Previous research suggests that the length of abstinence from cocaine affects

neurocognitive functioning in cocaine-dependent participants. For example, on one

particular test of executive function, impairment was noted 2-4 weeks following the last

cocaine use (Ardila, Rosselli, & Strumwasser, 1991) whereas this impairment was not

present during shorter periods of abstinence (within 3 days of last drug use) (Berry et al.,

1993). Another factor that needs to be considered as well is co-morbid substance abuse,

including cigarettes, alcohol, and marijuana. When compared to healthy control subjects,

cocaine-dependent individuals are more likely to smoke cigarettes, and the frequency of

cigarette smoking is positively correlated with their concurrent use of cocaine (Budney,

Higgins, Hughes, & Bickel, 1993; Roll, Higgins, Budney, Bickel, & Badger, 1996).

Neurocognitive deficits, including attention, memory, executive and motor functions,

are commonly impaired in alcohol-dependent individuals (Beatty, Tivis, Stott, Nixon, &

Parsons, 2000; Ikeda et al., 2003; Parsons & Nixon, 1993); however, there has not been

a wealth of literature exploring the neurocognitive effects of concurrent cocaine and

alcohol use. In addition, marijuana use interferes with memory as well as a variety of

cognitive processes, including attention and processing speeding (Pope & Yurgelun-

Todd, 1996). While the impact of other substances, such as nicotine, alcohol, and

6

marijuana, on neurocognition has been reported in the literature, the impact of concurrent

cocaine use and those substances on neurocognition has not yet been discussed.

One critical question is whether stimulant-induced neurocognitive impairment can

be reversed or ameliorated using cognition enhancing interventions. For example,

following administration of 20 mg of oral methylphenidate (a medication used to enhance

cognitive functioning in individuals with attention deficit/hyperactivity disorder),

cocaine-dependent individuals made fewer errors on a computerized cognitive salience

task (in which participants viewed a drug-related or neutral word on a screen written in

blue, green, red, or yellow font, then pressed the matching colored button on a key pad)

(Goldstein et al., 2010). Similarly, in a sample of methamphetamine-dependent

individuals who demonstrated relatively poor neurocognitive performance at baseline,

administration of 400 mg of modafinil for three days significantly improved response

accuracy on measures of working memory in study participants (Kalechstein, De La

Garza, & Newton, 2010). Another study in methamphetamine-dependent volunteers

showed that a single dose of 200 mg modafinil improved performance on a reversal

learning task (Ghahremani, Tabibnia, Monterosso, Hellemann, Poldrack, & London,

2011). Similarly, the results of a recent study indicate that modafinil improved working

memory in cocaine-dependent individuals, measured by the n-back task (Kalechstein,

Yoon, Mahoney, & De La Garza, 2012).

Several reasons support the decision to focus on treating cocaine-induced

neurocognitive impairment not only with medications such as methylphenidate or

modafinil, but also acetylcholinesterase inhibitors such as rivastigmine and huperzine.

For example, rivastigmine is a cognition-enhancing agent used for the treatment of

7

Alzheimer’s disease (Hasselmo & Sarter, 2011) and, in double-blind, placebo-controlled

studies, administration of rivastigmine was associated with improved performance on

tests of attention and memory in individuals diagnosed with Alzheimer’s disease

(Feldman & Lane, 2007; Frankfort et al., 2007) and traumatic brain injury (Silver et al.,

2009; Tenovuo, Alin, & Helenius, 2009). In these studies, the efficacy of rivastigmine

was greatest at higher doses (Silver et al., 2009); however, because the efficacy of

rivastigmine has not been evaluated in cocaine-dependent individuals, we sought to

determine whether relatively low-dose, short-term administration of rivastigmine would

be associated with improved performance on measures of attention, information

processing speed, episodic memory, and working memory in this population.

A separate acetylcholinesterase inhibitor, huperzine, has been evaluated in several

trials involving several hundred human patients (Li, Wu, Zhou, Liu, & Dong, 2008;

Little, Walsh, & Aisen, 2008; Wang, Yan, & Tang, 2006; Zangara, 2003). Of particular

interest, huperzine has been shown to ameliorate deficits in learning and memory. A trial

investigating potential treatments for Alzheimer’s disease revealed that huperzine

significantly improved memory deficits in elderly people with benign senescent

forgetfulness and in patients with Alzheimer’s disease and vascular dementia. These

beneficial effects were observed with minimal peripheral cholinergic side effects and no

unexpected toxicity, demonstrating that it is not only efficacious, but also safe and well-

tolerated.

In conclusion, acetylcholinesterase inhibitors have been shown to improve

cognition, reinforcing that these agents may be similarly useful in treating substance

abuse disorders, specifically cocaine-dependence. Ameliorating these cognitive deficits

8

is of great relevance and importance since exposure to cocaine and other drugs of abuse

is associated with cognitive deficits in humans, and, as mentioned earlier, intact cognitive

functioning has been shown to be positively associated with favorable outcomes in

outpatient clinical trials in cocaine-dependent subjects (Aharonovich, Nunes, & Hasin,

2003).

Research Questions

1. Do gender differences exist with regard to neurocognitive functioning in cocaine-

dependent individuals?

2. Do race differences exist with regard to neurocognitive functioning in cocaine-


3. Does comorbid substance use (e.g. nicotine, alcohol, marijuana) exacerbate

neurocognitive deficits in cocaine-dependent individuals?

4. What is the relationship between drug use variables (e.g. years of cocaine use,

days cocaine used in the past 30, etc.) and neurocognitive functioning in cocaine-


5. What is the relationship between mood variables (e.g. BDI-II, LSC-R, and ASI-

Lite scores) and neurocognitive functioning in cocaine-dependent individuals?

6. Do two different acetylcholinesterase inhibitors (rivastigmine and huperzine) have

the capability of improving neurocognitive functioning and ameliorating deficits

in cocaine-dependent individuals?

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Hypotheses

1. It is hypothesized that males and females will differ in neurocognitive tasks, with

females significantly outperforming males on tests of attention and verbal

memory.

2. Based on the literature in non-drug using controls, when matching for education

and IQ, it is hypothesized that Caucasians will perform comparably on various

neurocognitive tests when compared to their African American counterparts.

3. It is hypothesized that comorbid substance use will result in further

neurocognitive deficits then when compared to those whom only use cocaine.

4. It is hypothesized that that there will be a significantly negative correlation

between the drug use variables (e.g. years of cocaine use, amount of cocaine used

per day, etc.) and neurocognitive functioning across a variety of domains.

5. It is hypothesized that that there will be a significantly negative correlation

between mood variables (e.g. BDI-II, LSC-R, and ASI-Lite scores) and

neurocognitive functioning across a variety of domains.

6. It is hypothesized that both rivastigmine and huperzine will significantly improve

various domains of neurocognitive functioning, including attention, verbal

memory, and working memory, when compared to placebo.

C. Implications

A major factor that detrimentally affects progress in treatment for cocaine-

dependent individuals seeking treatment is the presence of neurocognitive deficits

generated or exacerbated by cocaine use. Since long-term, high-dose cocaine use is a risk

10

factor for the onset of neurocognitive impairment in humans, it is critical that these

deficits be addressed in order to improve treatment outcomes. Specifically, deficits in

attention or memory may lead to unfavorable outcomes for several reasons. For example,

deficits in attention may cause the cocaine-dependent individual to be unable to maintain

focus, attend, and follow through on treatment plans and goals provided during the

therapy process. In addition, deficits in memory may cause these individuals to have a

difficult time remembering both the positive and negative times in their life or specific

techniques taught during treatment which would also impede their progress. Also,

deficits in memory may cause their reasoning, comprehension, and information

processing to be adversely affected causing less favorable treatment outcomes. Thus, it is

important to take these factors and neurocognitive deficiencies into consideration when

attempting to treat someone with cocaine-dependence. The implications of this study are

critical as they will not only determine whether the aforementioned candidate

medications are effective for treating neurocognitive impairments, but will also determine

which demographic or drug use variables contribute to these neurocognitive deficits so

that appropriate treatment plans can be initiated.

CHAPTER III

METHODOLOGY

Procedure – Recruitment/Screening

Participants were recruited from the Houston metropolitan area through

newspaper and radio advertisements. The study was approved by the Baylor College of

Medicine and Michael E. DeBakey Veterans Association Medical Center (MEDVAMC)

Internal Review Boards. All participants completed an initial telephone screen in order to

assess basic eligibility. Candidates were then invited to complete an in-person assessment

at the Research Commons of the MEDVAMC. During the in-person interview,

candidates received an explanation of the study purpose and requirements and were

allowed to review, inquire about, and sign the informed consent form. Eligible

individuals were required to be between 18-55 years of age, provide at least one urine

specimen that was positive for cocaine within the two weeks prior to study enrollment,

met DSM-IV criteria for cocaine-dependence, and were experienced with respect to

smoking and/or injecting cocaine. Participants were excluded if they had psychiatric or

medical illness, serious neurological or seizure disorder, use of any psychoactive

medication, and drug or alcohol dependence excluding cocaine, marijuana, and nicotine.

Women were classified as ineligible for the study if they were pregnant, breast feeding,

or not using a reliable form of birth control. In addition, participants completed a

demographic/drug and alcohol use inventory, ASI-Lite, LSC-R, and BDI-II. Participants

were compensated with a $40 gift card for completing the in-person screen. These

recruitment and screening procedures described above were the same used for Study 2.

12

A. Procedure – Assessments

Drug and Alcohol Use Questionnaire

Drug use was assessed with a 14-item, self-report questionnaire with frequency

assessed in terms of date of last use, days used in the past 30, years of use, grams used

per day, and route of administration. In addition to cocaine, substance use frequency was

also assessed for alcohol, methamphetamine, opiates, marijuana, and nicotine. In

addition, recent drug use was assessed and confirmed via qualitative urine toxicology

(testing for cocaine metabolites, amphetamine, methamphetamine, marijuana, and

opiates).

Life Stressor Checklist- Revised (LSC-R)

The LSC-R (Wolfe & Kimerling, 1997) measures life stress in 30 areas that could

elicit PTSD responses (e.g., being mugged, the death of a loved one, a sexual assault).

The LSC-R assesses for whether or not each stressful event occurred, at what ages the

events occurred, how many times each event occurred, how dangerous the event was, and

whether the individual had an intense emotional reaction to the event(s). The total LSC-

R score is obtained by adding up the total number of experiences endorsed (thus the

range is 0 – 30 with 30 indicating endorsement of all experiences). There are 30 events

included on the checklist involving experiences such as natural disasters, assault, death of

family/friends, etc. It should be noted that some of the items are not necessarily

traumatic in nature, but would likely be stress-inducing. Test-retest reliability measures

indicate that kappa values range from 0.52-0.97 across life stress domains on the LSC-R

(McHugo et al., 2005). Additionally, the LSC-R has good concurrent validity with the

Impact of Event Scale – Revised (IES-R) and the Symptom Checklist – 90 – Revised

13

(SCL-90-R), as well as high agreement with clinician ratings (Ungerer et al., 2009). The

LSC-R has demonstrated good criterion validity for PTSD in populations with comorbid

mental health and substance abuse disorders (McHugo et al., 2005).

Addiction Severity Index-Lite (ASI-Lite)

The ASI-Lite (McLellan, Cacciola, Alterman, Rikoon, & Carise, 2006) is a

shortened version of the ASI which is a semi-structured assessment used to evaluate

lifetime and recent (past 30 days) problem behaviors. As mentioned earlier, the ASI-Lite

is divided into 7 separate composite scores: medical, employment, alcohol use, drug use,

family, legal, and psychiatric. The total ASI-Lite score, as well as the composite scores,

are intended to provide the clinician/researcher a more detailed perspective of issues

surrounding ongoing drug use. In general, the ASI-Lite has been found to have good

test-retest reliability with kappa values of approximately 0.60 (Drake & Noordsy, 1995).

Inter-rater reliability measures of the ASI-Lite range from 0.83-1.00 (Stoffelmayr Mavis

&, Kasim, 1994). In cocaine-dependent samples specifically, the ASI-Lite has shown

good test-retest reliability, especially in the domains of lifetime medical, psychiatric, and

substance abuse history (Cacciola, Koppenhaver, McKay, & Alterman 1999).

Beck Depression Inventory – II (BDI-II)

The BDI-II (Beck, 2006) is a 21-question, self-report inventory that evaluates the

presence of depressive symptoms, such as hopelessness and irritability, cognitions such

as guilt or feelings of being punished, as well as physical symptoms such as fatigue,

weight loss, and lack of interest in sex.

http://en.wikipedia.org/wiki/Self-report_inventory

http://en.wikipedia.org/wiki/Weight_loss

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B. Procedure – Neurocognitive Battery

Participants were provided with standardized instructions, both oral and written,

before the administration of each task. Additionally, participants were reminded to

respond as quickly and as accurately as possible. The tests were selected based on

studies demonstrating that these and or similar measures were shown to be valid and

reliable with respect to differentiating between cocaine-dependent individuals and

matched controls (Gooding, Burroughs, & Boutros, 2008; Verdejo-Garcia, Vilar-Lopez,

Perez-Garcia, Podell, & Goldberg, 2006).

Wechsler Adult Intelligence Scale-III (WAIS-III). The Vocabulary and Matrix

Reasoning subtests of the WAIS-III were administered. The raw scores from these

subtests were included in an algorithm, the Oklahoma Premorbid Intelligence Estimation

algorithm (Schoenberg, Scott, Duff, & Adams, 2002), which estimates level of

intellectual function prior to the onset of drug use (Wechsler, 2007).

Continuous Performance Test-II (CPT- II). The CPT-II measures sustained

attention. Participants were instructed to press the space bar whenever any letter, except

for X, appeared on the computer screen. The letters were presented for 250 milliseconds,

and new letters appeared at intervals of 1, 2, or 4 seconds. The inter-stimuli time intervals

varied pseudo-randomly.

The variables of interest included three measures of inattention: sensitivity – level

of discrimination between signal (X) and non-signal responses; omissions – failure to

press the space bar when letters other than X appear; and hit rate – reaction time in

milliseconds for correct responses. The indices will be transformed into standard scores,

i.e. T-scores, for the data analysis (Conners, 2002).

15

Hopkins Verbal Learning Test-Revised (HVLT-R). The HVLT-R is a measure of

verbal learning and memory that includes six different forms. Participants were initially

read a list of 12 words, approximately one word per second, and asked to repeat back as

many words as possible. This procedure was repeated twice, for a total of three learning

trials. Following a 20 to 25 minute delay period (the Dual N-Back assessment was

administered during the delay period), participants were asked to recall the words without

the aid of reminders. The 2 dependent variables of interest for the HVLT-R were the

standard scores (T-scores) for the total words recalled during all of the three learning

trials and the number of words remembered following the 20 to 25 minute delay period

(Brandt, 2005).

Dual N-back Task. For this computerized working memory task developed by

Susanne Jaeggi, participants were presented with a series of visual stimuli (blue squares)

and auditory stimuli (letters) simultaneously presented across 20 blocks of 21 trials each.

The visual stimulus was presented in one of eight locations on the screen, and the

auditory stimulus was one of eight different letters. For each trial, stimuli were presented

simultaneously for 500 milliseconds, with a 2500 millisecond latency period between the

presentation of stimuli.

Participants started with the 1-back condition, where they were required to

provide a "yes” response (pressing a blue button with the left forefinger) if the location of

the presented visual stimulus matched the location of the stimulus presented immediately

beforehand. Similarly, if the auditory stimulus matched the stimulus presented

immediately beforehand, the participants were required to provide a "yes" response

(pressing a red button with the right forefinger). If both the visual and auditory stimuli

16

matched those presented in the previous trial, then participants were expected to

concurrently press the red and blue buttons, and finally, no response was required if none

of the stimuli matched.

While completing the 20 blocks, the task difficulty varied as a function of

participants’ performance. Specifically, if participants achieved at least 90% accuracy

rate for both visual and auditory modalities in a particular block, the n-back level

increased by one (e.g., from 1-back to 2-back). Conversely, participants regressed to

simpler conditions, e.g., from 2-back to 1-back, if they achieved less than 70% accuracy

for either the visual and auditory modalities in a particular block. Finally, the n-back level

stayed the same if participants performed at an accuracy level between 70 and 90%. For

all levels, a "yes” response was required if the presented visual stimulus or auditory

stimulus matched the stimulus that was presented n trials previously. Dependent

variables were mean n-back level reached in those 20 + n blocks, maximum n-back level

reached, visual accuracy, and auditory accuracy (defined as the ratio of accurate

responses to total responses) (Jaeggi, Buschkuehl, Jonides, & Perrig, 2008).

Order of Test Administration: The battery of neurocognitive tests were administered in

the following order: the HVLT-R learning recall trials, the dual N-back tests, delayed

recall of the HVLT-R, and lastly the CPT-II. The average duration of these

neurocognitive procedures was an hour and a half. The reaction time tests were

programmed on a laptop computer. The WAIS-III was administered on a separate day,

after verifying that the volunteer was not experiencing withdrawal symptoms from

cocaine, and before randomization into the study arms.

17

C. Study 1 - Overview

This study investigated the demographic (e.g. gender, ethnicity, age), drug use

(e.g. years, recent, and daily cocaine use and smoking status) variables that may affect

neurocognition. In addition, we also investigated other variable such as LSC-R, ASI-

Lite, and BDI-II scores and their potential impact on neurocognition.

Study 1 - Participants

The final sample size for Study 1 included 125 cocaine-dependent participants

who were not seeking treatment for their cocaine-dependence at time of the assessment.

Study 1 - Procedures

All eligible participants who completed a baseline neurocognitive battery (before

randomization to one of the many study medication evaluated in the laboratory) were

included in this study.

Study 1 - Statistical Analysis

To alleviate the potential confound of demographic and drug use variability when

assessing gender differences, female cocaine users (n= 21) were matched with male

counterparts (n= 21) on the following variables: age, education, IQ, years of stimulant

use, recent stimulant use, and amount of stimulant used per day. In similar fashion,

Caucasians (n= 16) were matched with their African Americans counterparts to

determine race differences, non-cigarette smokers (n= 17) were matched with cigarette

smokers to determine the impact of cigarette smoking on neurocognitive performance,

alcohol users (n= 15) were matched with non-alcohol users to determine the impact of

alcohol use on neurocognitive performance, and marijuana smokers (n= 20) were

matched with non-marijuana smokers to determine the impact of marijuana smoking on

18

neurocognitive performance. One-way analysis of variance (ANOVA) was utilized to

detect gender, race, or other drug use differences on neurocognition. Since females,

Caucasians, non-smokers, non-dependent alcohol and marijuana users rarely enroll in our

ongoing studies for cocaine-dependent individuals, the distribution was skewed, which

served as the rationale for matching these participants to an equal number of their

counterparts on the aforementioned characteristics. Pearson product moment correlations

were used to evaluate the association between continuous demographic variables (e.g.

age, education, and IQ) and performance on neurocognitive measures. Similarly, Pearson

product moment correlations were used to evaluate the association between continuous

drug use variables (e.g. years of cocaine use, recent cocaine use in the past 30 days, and

daily use of cocaine in grams) and performance on the neurocognitive measures. In

addition, Pearson product moment correlations were used to evaluate the association

between mood symptoms, stress, and addiction severity (e.g. BDI-II, LSC-R, ASI-Lite

scores) and performance on the neurocognitive measures. For demographic, drug use,

and mood comparisons, significance was set at p < 0.05, and when assessing

neurocognitive performance, significance was set at p < 0.006 after incorporating a

Bonferroni correction for multiple comparisons. All analyses were conducted with SPSS

version 17.

Study 2 - Overview

This study investigated the independent efficacy of rivastigmine and huperzine as

potential treatments to ameliorate cocaine-induced neurocognitive impairment.

D. Study 2 - Participants

The sample size for Study 2 included 72 cocaine-dependent participants who were

19

not seeking treatment for their cocaine-dependence at time of the assessment.

Study 2 - Procedures

The study involved a between-subjects, double-blind, placebo-controlled design.

Baseline neurocognitive testing was performed on Day 0 prior to randomization to study

medication. Medication of placebo was administered twice daily beginning on Day 2. 28

participants were randomized to rivastigmine, 29 participants were randomized to

huperzine, and 15 were randomized to placebo. Neurocognitive testing was repeated on

Day 9 following seven days of medication administration which was sufficient for each

drug to reach steady state levels.

Study 2 - Statistical Analysis

Initially, if there were differences between groups at baseline, a within-subjects,

repeated measures ANOVA would have been utilized to evaluate the effects of

rivastigmine, huperzine, and placebo on test performance at baseline (Day 0) and at the

point in time at which sustained rivastigmine or huperzine exposure results in peak blood

levels of the medication (Day 9). However, after preliminary analysis, there were no

differences between any of the groups at baseline (Day 0) so only post-medication (Day

9) groups were compared using one-way ANOVA. For demographic and drug use

comparisons, significance was set at p < 0.05, and when assessing neurocognitive

performance, significance was set at p < 0.006 after incorporating a Bonferroni correction

for multiple comparisons. All analyses were conducted with SPSS version 17.

CHAPTER IV

RESULTS

A. Study 1 – Demographic and drug use variables which may affect neurocognition

Demographic and drug use characteristics for the entire sample (n = 125) can

be found in Table 1. Cocaine-dependent participants were primarily African American

and ~45 years of age. Participants reported using cocaine for ~18 years, 17 days out of

the last 30, and used ~2.0 grams of cocaine/day. A majority of participants also reported

concurrent use of nicotine, alcohol, and/or marijuana.

21

Table 1

Demo/Drug Use Statistics and overall Neurocognitive Performance for the entire sample

Participant Characteristics Cocaine-Dependent Pts

(N = 125)

Demographics

Males

Females

104 (83%)

21 (17%)

Caucasian

African American

29 (23%)

96 (77%)

Age (years) 44.9±0.60

Education (years) 12.4±0.1

IQ (WAIS-III) 97.7±1.1

Drug Use

Cocaine

Years of use

Days used in past 30

Grams per day

100%

17.5±0.7

16.7±0.8

2.0±0.2

Cigarette

Years of Use

Cigarettes/day

86%

22.6±0.8

13.6±0.8

Alcohol

Years of Use


89%

21.3±0.9

10.4±0.9

Marijuana

Years of Use


64%

18.8±1.2

5.0±0.9

Neurocognitive Performance

CPT-II Performance

D’ (Sensitivity) 49.74±0.81

Hit Rate – RT^ 49.85±1.27

Omissions^^ 66.58±3.02

HVLT-R Performance

Trials 1-3 36.78±0.96

Delayed Recall 39.14±1.07

N-Back Performance

Auditory Accuracy 0.58±0.02

Visual Accuracy 0.46±0.01

N-value (mean) 1.42±0.03

N-value (max) 2.02±0.06

Values represent Mean±SEM

^RT=reaction time

^^Higher scores are indicative of poorer performance

22

Neurocognitive Functioning in Males versus Females

When investigating neurocognitive differences between genders, cocaine-

dependent males (n=21) and females (n= 21) were statistically similar with regard to all

demographic/drug use variables (Table 2). Cocaine-dependent participants were

primarily African American and ~42 years of age. Participants reported using cocaine for

~15 years, ~15 days out of the last 30, and used ~2.0 grams of cocaine/day.

Males and females did not differ on measures of sustained attention as

measured by the CPT, including sensitivity (F1,40 = 0.368, p = 0.548), hit rate (F1,40 =

1.670, p = 0.204), and omissions (F1,40 = 1.178, p = 0.284). In addition, males and

females scored similarly on measures of immediate episodic memory (F1,40 = 1.858, p =

0.181) nor delayed episodic memory (F1,40 = 4.536, p = 0.039) as measured by the HVLT.

Finally, males and females did not differ on indices of working memory as measured by

the dual n-back, including mean length of the n-back trials for each block working

memory (F1,40 = 0.114, p = 0.738), maximum block length during each assessment (F1,40 =

0.780, p = 0.382), accuracy of responding to auditory stimuli (F1,40 = 0.383, p = 0.540),

and accuracy of responding to visual stimuli (F1,40 = 0.429, p = 0.516).

23

Table 2

Neurocognitive Functioning in Males versus Females

Participant Characteristics

Males

(N = 21)

Females

(N = 21)

p

Demographics

Males

Females

21 (100%)

0

0

21 (100%)

Caucasian

African American

6 (29%)

15 (71%)

6 (29%)

15 (71%)

Age (years) 41.5±1.4 43.9±1.5 .26

Education (years) 11.8±0.3 12.3±0.5 .39

IQ (WAIS-III) 96.3±3.2 93.5±3.4 .56

Drug Use

Cocaine

Years of use


Grams per day

16.3±1.4

16.5±1.9

2.1±0.7

15.0±2.1

15.4±2.1

2.0±0.4

.59

.71

.97

Cigarette

Years of Use

Cigarettes/day

95% 86%

20.7±1.6

13.2±1.9

22.4±2.5

15.7±1.9

.56

.83

Alcohol

Years of Use


86% 86%

16.8±1.9

11.6±2.4

18.8±2.5

9.8±2.6

.55

.63

Marijuana

Years of Use


62% 52%

20.3±2.4

6.6±2.6

13.7±3.3

6.3±2.9

.11

.93


CPT-II Performance

D’ (Sensitivity) 51.85±1.79 49.97±2.53 .55

Hit Rate – RT^ 44.49±3.83 50.47±2.61 .20

Omissions^^ 59.17±5.43 68.03±6.09 .28

HVLT-R Performance

Trials 1-3 35.62±2.11 39.90±2.33 .18

Delayed Recall 35.57±2.59 43.10±2.41 .04

N-Back Performance

Auditory Accuracy 0.61±0.22 0.56±0.24 .54

Visual Accuracy 0.43±0.03 0.46±0.03 .52

N-value (mean) 1.40±0.10 1.36±0.07 .74

N-value (max) 2.05±0.18 1.86±0.13 .38


^RT=reaction time


*p<0.05

**p<0.006

24

Neurocognitive Functioning in African Americans versus Caucasians

When investigating neurocognitive differences between races, cocaine-dependent

African Americans (n = 16) and Caucasians (n = 16) were statistically similar with regard

to all demographic/drug use variables with the exception of years of nicotine use (F1,28 =

5.461, p = 0.027), cigarettes per day (F1,28 = 11.567, p=0.002), and years of marijuana use

(F1,22 = 5.467, p = 0.029) where Caucasians reported using significantly more cigarettes

and marijuana than African Americans (Table 3). Cocaine-dependent participants were

primarily male and ~43 years of age. Participants reported using cocaine for ~16 years,

~17 days out of the last 30, and used ~2.5 grams of cocaine/day.

African Americans and Caucasians did not differ on measures of sustained

attention as measured by the CPT, including sensitivity (F1,30 = 2.884, p = 0.100), hit rate

(F1,30 = 0.151, p = 0.700), omissions (F1,30 = 0.135, p = 0.716). In addition, African

Americans and Caucasians did not differ on measures of immediate or delayed episodic

memory. Specifically, African Americans and Caucasians did not differ with respect to

performance over three learning trials (F1,30 = 0.004, p = 0.951), nor did they differ

following a 15 minute delay period (F1,30 = 0.122, p = 0.730). Finally, African

Americans and Caucasians did not differ on indices of working memory as measured by

the dual n-back, including mean length of the n-back trials for each block working

memory (F1,30 = 2.543, p = 0.0121), maximum block length during each assessment

(F1,30 = 0.429, p = 0.518), accuracy of responding to auditory stimuli (F1,30 = 0.293, p =

0.592), and accuracy of responding to visual stimuli (F1,30 = 0.459, p = 0.503).

25

Table 3

Neurocognitive Functioning in African Americans versus Caucasians


African- American

(N = 16)

Caucasian

(N = 16)

p

Demographics

Males

Females

14 (88%)

2 (12%)

13 (81%)

3 (19%)

Caucasian

African American

0

16 (100%)

16 (100%)

0

Age (years) 43.1±0.50 43.2±1.9 .98

Education (years) 12.6±0.3 12.9±0.5 .50

IQ (WAIS-III) 99.1± 3.15 102.0±2.39 .48

Drug Use

Cocaine

Years of use


Grams per day

16.8±1.2

17.8±2.0

2.5±0.9

15.8±2.5

16.8±2.7

2.5±1.0

.74

.76

.98

Cigarette

Years of Use

Cigarettes/day

100% 88%

19.4±1.8

10.6±1.5

26.1±2.2

18.6±1.9 .03*

.002** Alcohol

Years of Use


88% 94%

19.9±2.1

11.6±2.3

25.8±2.2

8.7±2.5

.06

.42

Marijuana

Years of Use


81% 69%

14.2±2.7

1.5±0.4

23.3±2.7

6.0±2.7 .03*

.09


CPT-II Performance

D’ (Sensitivity) 49.86±1.83 54.51±2.03 .10

Hit Rate – RT^ 47.60±3.36 45.60±3.89 .70

Omissions^^ 58.44±5.04 60.85±4.19 .72

HVLT-R Performance

Trials 1-3 39.25±2.49 39.0±3.19 .95

Delayed Recall 42.60±3.16 41.13±2.82 .73

N-Back Performance


Visual Accuracy 0.48±0.04 0.51±0.02 .50

N-value (mean) 1.41±0.07 1.57±0.08 .12

N-value (max) 2.13±0.13 2.25±0.14 .52


^RT=reaction time


*p<0.05

**p<0.006

26

Neurocognitive Functioning in Cigarette Smokers versus Non-Cigarette Smokers

When investigating neurocognitive differences between cigarette smokers and

non-smokers, cocaine-dependent cigarette smokers (n = 17) and non-cigarette smokers (n

= 17) were statistically similar with regard to all demographic/drug use variables with the

exception of years (F1,27 = 6.995, p = 0.013) and recent alcohol use (F1,27 = 4.236, p =

0.049) (Table 4). Cocaine-dependent participants were primarily male, African

American and ~46 years of age. Participants reported using cocaine for ~17 years, ~16

days out of the last 30, and used ~2.0 grams of cocaine/day. Those cigarette smokers

included in the analyses reporting using cigarettes for ~27 years and smoked ~23

cigarettes per day.

Cigarette smokers and non-cigarette smokers did not differ on measures of

sustained attention as measured by the CPT, including sensitivity (F1,32 = 0.609, p =

0.441), hit rate (F1,32 = 0.305, p = 0.584), and omissions (F1,32 = 0.040, p = 0.844). In

addition, cigarette smokers and non-cigarette smokers did not differ on measures of

immediate or delayed episodic memory. Specifically, cigarette smokers and non-

cigarette smokers did not differ with respect to performance over three learning trials

(F1,32 = 0.178, p = 0.676), nor did they differ following a 15 minute delay period (F1,32 =

0.034, p = 0.855). Finally, cigarette smokers and non-cigarette smokers did not differ on

indices of working memory as measured by the dual n-back, including mean length of the

n-back trials for each block working memory (F1,32 = 0.373, p = 0.545), maximum block

length during each assessment (F1,32 = 2.299, p = 0.139), accuracy of responding to

auditory stimuli (F1,32 = 1.381, p = 0.249), and accuracy of responding to visual stimuli

(F1,32 = 0.809, p = 0.375).

27

Table 4

Neurocognitive Functioning in Cigarette Smokers versus Non-Smokers


^RT=reaction time


*p<0.05

**p<0.006

Participant Characteristics Smoker

(N = 17)

Non-Smoker

(N = 17)

p

Demographics

Males

Females

14 (82%)

3 (18%)

14 (82%)

3 (18%)

Caucasian

African American

4 (12%)

13 (76%)

6 (35%)

11 (65%)

Age (years) 46.7±1.1 46.6±1.2 .94

Education (years) 12.5±0.3 12.5±0.3 .90

IQ (WAIS-III) 98.3±3.0 99.3±3.4 .84

Drug Use

Cocaine

Years of use


Grams per day

17.6±2.1

18.8±2.4

1.8±0.3

17.8±1.8

14.0±2.0

1.8±0.3

.97

.13

.97

Cigarette

Years of Use

Cigarettes/day

27.0±7.9

22.8±5.6

-

- <.001**

<.001** Alcohol

Years of Use


76% 94%

24.9±2.9

14.2±3.5

16.2±1.8

6.6±1.8 .01*

.05* Marijuana

Years of Use


47% 41%

20.9±4.3

2.4±1.0

19.0±2.2

5.1±4.2

.70

.52


CPT-II Performance

D’ (Sensitivity) 50.91±1.98 53.23±2.22 .44

Hit Rate – RT^ 49.60±3.98 46.70±3.42 .58

Omissions^^ 68.38±6.89 71.11±11.88 .84

HVLT-R Performance

Trials 1-3 37.88±3.07 36.24±2.42 .68

Delayed Recall 39.35±2.49 38.63±3.09 .86

N-Back Performance


Visual Accuracy 0.44±0.03 0.47±0.03 .38

N-value (mean) 1.37±0.07 1.43±0.09 .55

N-value (max) 1.82±.0.13 2.12±0.15 .14

28

Neurocognitive Functioning in Alcohol Drinkers versus Non-Drinkers

When investigating neurocognitive differences between alcohol users and non-

users, cocaine-dependent alcohol users (n = 15) and non-alcohol users (n = 15) were

statistically similar with regard to all demographic/drug use variables (Table 5).

Cocaine-dependent participants were primarily male, African American and ~44 years of

age. Participants reported using cocaine for ~15 years, ~20 days out of the last 30, and

used ~2.0 grams of cocaine/day. Those alcohol users included in the analyses reporting

using alcohol for ~25 years and ~25 days out of the past 30.

Alcohol users and non-alcohol users did not differ on measures of sustained

attention as measured by the CPT, including sensitivity (F1,28 = 0.668, p = 0.421), hit rate

(F1,28 = 2.630, p = 0.116), and omissions (F1,28 = 0.005, p = 0.945). In addition, alcohol

users and non-alcohol users did not differ on measures of immediate or delayed episodic

memory. Specifically, alcohol users and non-alcohol users did not differ with respect to

performance over three learning trials (F1,28 = 0.187, p = 0.669); nor did they differ

following a 15 minute delay period (F1,28 = 0.151, p = 0.700). Finally, alcohol users and

non-alcohol users did not differ on indices of working memory as measured by the dual

n-back, including mean length of the n-back trials for each block working memory (F1,28

= 0.360, p = 0.554), maximum block length during each assessment (F1,28 = 1.923, p =

0.176), accuracy of responding to auditory stimuli (F1,28 = 0.819, p = 0.373), and accuracy

of responding to visual stimuli (F1,28 = 0.275, p = 0.604).

29

Table 5

Neurocognitive Functioning in Alcohol Drinkers versus Non-Drinkers


Drinker

(n = 15)

Non-Drinker

(n = 15)

p

Demographics

Males

Females

10 (67%)

5 (33%)

12 (80%)

3 (20%)

Caucasian

African American

7 (47%)

8 (53%)

3 (20%)

12 (80%)

Age (years) 44.2±2.1 44.6±1.9 .89

Education (years) 12.5±0.4 11.9±0.4 .31

IQ (WAIS-III) 98.9±2.0 92.0±3.7 .11

Drug Use

Cocaine

Years of use


Grams per day

17.7±2.6

19.9±2.0

1.6±0.3

13.1±1.6

20.3±1.7

2.3±0.4

.14

.88

.15

Cigarette

Years of Use

Cigarettes/day

87% 93%

23.9±2.7

14.7±1.8

21.3±2.4

13.3±2.2

.48

.63

Alcohol

Years of Use


24.6±2.3

24.3±1.1

-

- <.001**

<.001** Marijuana

Years of Use


67% 53%)

15.8±3.5

3.0±2.5

14.6±3.7

6.3±3.4

.81

.43


CPT-II Performance

D’ (Sensitivity) 50.05±2.55 52.90±2.39 .42

Hit Rate – RT^ 48.52±2.92 41.58±3.12 .12

Omissions^^ 59.13±6.05 59.66±4.46 .95

HVLT-R Performance

Trials 1-3 38.47± 2.74 36.93±2.25 .67

Delayed Recall 42.27± 2.93 40.73±2.64 .70

N-Back Performance


Visual Accuracy 0.47±0.05 0.44±0.03 .60

N-value (mean) 1.46±0.08 1.38±0.11 .55

N-value (max) 2.20±0.18 1.87±0.17 .18


^RT=reaction time


*p<0.05

**p<0.006

30

Neurocognitive Functioning in Marijuana Smokers versus Non-Smokers

When investigating neurocognitive differences between marijuana smokers and

non-smokers, cocaine-dependent marijuana smokers (n = 20) and non-marijuana smokers

(n= 20) were statistically similar with regard to all demographic/drug use variables

(Table 6). Cocaine-dependent participants were primarily male, African American and

~43 years of age. Participants reported using cocaine for ~14 years, ~18 days out of the

last 30, and used ~2.0 grams of cocaine/day. Those marijuana users included in the

analyses reporting using marijuana for ~24 years and ~16 days out of the past 30.

Marijuana smokers and non-marijuana smokers did not differ on measures of

sustained attention as measured by the CPT, including sensitivity (F1,38 = 0.199, p =

0.658), hit rate (F1,38 = 0.070, p = 0.792), and omissions (F1,38 = 0.529, p = 0.471). In

addition, marijuana smokers and non-marijuana smokers did not differ on measures of

immediate or delayed episodic memory. Specifically, marijuana smokers and non-

marijuana smokers did not differ with respect to performance over three learning trials

(F1,38 = 1.157, p = 0.289), nor did they differ following a 15 minute delay period (F1,38 =

1.964, p = 0.169). Finally, marijuana smokers and non-marijuana smokers did not differ

on indices of working memory as measured by the dual n-back, including mean length of

the n-back trials for each block working memory (F1,38 = 0.063, p = 0.804), maximum

block length during each assessment (F1,38 = 0.239, p = 0.628), accuracy of responding to

auditory stimuli (F1,38 = 0.976, p = 0.329), and accuracy of responding to visual stimuli

(F1,38 = 0.086, p = 0.771).

31

Table 6

Neurocognitive Functioning in Marijuana Smokers versus Non-Smokers


Marijuana

(n = 20)

Non-Marijuana

(n = 20)

p

Demographics

Males

Females

17 (85%)

3 (15%)

16 (80%)

4 (20%)

Caucasian

African American

6 (30%)

14 (70%)

5 (20%)

15 (75%)

Age (years) 43.3±2.0 42.1±1.5 .65

Education (years) 12.2±0.3 12.2±0.2 1.00

IQ (WAIS-III) 95.8±11.6 97.5±12.3 .68

Drug Use

Cocaine

Years of use


Grams per day

15.8±1.8

20.4±1.8

1.5±0.2

13.7±1.1

16.3±1.5

1.6±0.2

.33

.09

.72

Cigarette

Years of Use

Cigarettes/day

85% 85%

23.5±2.3

13.5±1.6

20.1±1.9

11.7±1.7

.27

.45

Alcohol

Years of Use


90% 80%

21.1±1.9

9.2±2.0

16.6±2.5

7.6±1.6

.15

.54

Marijuana

Years of Use


24.2±7.52

16.2±8.58

-

- <.001**

<.001**


CPT-II Performance

D’ (Sensitivity) 49.58±2.20 48.08± 2.51 .66

Hit Rate – RT^ 50.29±3.34 48.90± 4.01 .79

Omissions^^ 71.00±9.47 62.59± 6.63 .47

HVLT-R Performance

Trials 1-3 33.25±2.0 36.0± 1.59 .29

Delayed Recall 34.65±2.40 39.42± 2.41 .17

N-Back Performance


Visual Accuracy 0.44±0.03 0.45±0.04 .77

N-value (mean) 1.44±0.09 1.41±0.08 .80

N-value (max) 1.95±0.15 2.05±0.14 .63


^RT=reaction time


*p<0.05

**p<0.006

32

Correlations between Demographic, Drug Use, and Mood Variables and Neurocognitive

Performance

Despite considerable heterogeneity in responses among participants, Pearson

product-moment correlation revealed that age was negatively and significantly correlated

with mean length of the n-back trials for each block working memory (p < 0.001) and

maximum length of the n-back trials for each block of working memory; however, the r

values were very low (r < 0.400 for all measures) indicating that these relationships were

more likely explained by other factors. Pearson product-moment correlation revealed

that IQ was positively and significantly correlated with respect to episodic memory

performance over three learning trials (p < 0.001), delayed performance over three

learning trials (p < 0.001), accuracy of responding to auditory stimuli (p < 0.001), mean

length of the n-back trials for each block working memory (p < 0.001), maximum block

length during each assessment (p < 0.001); however, the r values were all quite low (r <

0.460 for all measures) indicating that these relationships were more likely explained by

other factors. All other demographic, drug use, and mood variables were not

significantly correlated with neurocognitive performance (p>0.006).

33

Table 7

Correlations between Demographic, Drug Use, and Mood Variables and Neurocognitive Performance

Demographic Cocaine Use Mood

Age Education IQ Years Recent Daily BDI LSC-R ASI

CPT-II

D’ (Sensitivity) -.135 .058 .036 -.044 -.114 .022 -.010 .148 .108

Hit Rate – RT^ .190 -.082 -.040 .127 .026 -.172 .024 -.010 .029

Omissions^^ .056 .023 .083 .052 -.066 .076 -.017 .013 .043

HVLT-R

Trials 1-3 .004 .077 .437* .089 -.013 .163 -.062 -.067 .015

Delayed Recall -.041 .056 .348* -.047 -.102 .122 -.125 -.071 .009

N-Back

Auditory Accuracy -.099 .021 .176 -.157 -.039 .120 -.096 .029 -.056

Visual Accuracy -.152 -.005 .418* .135 .172 -.007 .018 .093 .161

N-value (mean) -.379* .178 .455* -.065 .147 -.091 -.025 .153 .172

N-value (max) -.335* .115 .422* -.081 .065 -.108 -.041 .132 .180


^RT=reaction time


*p<0.006

34

B. Study 2 – Rivastigmine and Huperzine as treatments for neurocognitive

impairment

Demographic and drug use characteristics of the 72 completers in the treatment

groups are presented in Table 8. A total of 75 participants were enrolled in the study (3

participants withdrew for personal reasons). Cocaine-dependent participants were

primarily African American and ~43 years of age. Participants reported using cocaine for

~16 years, 18 days out of the last 30, and used ~2 grams of cocaine/day. The treatment

groups did not differ for any basic demographic or drug use variables (all p-values >

0.05).

Preliminary analyses revealed that demographic indices, including age, years of

education, estimated level of premorbid IQ, and substance use indices, including lifetime

and recent use of alcohol, cocaine, and nicotine, did not correlate with performance on

indices of sustained attention, learning and memory, or working memory performance

(all p’s > 0.05). Thus, no covariates were included in the primary analyses.

The effects of rivastigmine on neurocognitive functioning

Table 9 includes the results of performance on measures of sustained attention,

episodic memory, and working memory when comparing those participants receiving 3

or 6 mg rivastigmine and placebo.

Participants randomized to rivastigmine versus placebo did not differ on measures

of sustained attention as measured by the CPT, including sensitivity (F1,41 = 0.014, p =

0.908), hit rate (F1,41 = 0.280, p = 0.600), omissions (F1,41 = 0.016, p = 0.899). However,

rivastigmine administration was associated with significantly improved performance on

measures of immediate memory. Specifically, participants randomized to rivastigmine

35

had significantly elevated performance over three learning trials (F1,41 = 11.856, p <

0.001). However, there were no differences between groups on performance following a

15 minute delay period (F1,41 = 1.947, p = 0.170). Rivastigmine administration was not

associated with significantly improved performance on two indices of working memory,

including mean length of the n-back trials for each block working memory (F1,41 = 5.010,

p = 0.031) and maximum block length during each assessment (F1,41 = 7.493, p = 0.009).

Rivastigmine and placebo groups did not differ on accuracy of responding to auditory

stimuli (F1,41 = 3.884, p = 0.056) nor accuracy of responding to visual stimuli (F1,41 =

0.911, p = 0.345).

The effects of huperzine on neurocognitive functioning

Table 10 includes the results of performance on measures of sustained attention,

episodic memory, and working memory when comparing those participants receiving 0.4

or 0.8 mg huperzine and placebo.

Participants randomized to 0.4 or 0.8 mg huperzine and placebo did not differ on

measures of sustained attention as measured by the CPT, including sensitivity (F1,42 =

0.226, p = 0.637), hit rate (F1,42 = 0.046, p = 0.831), and omissions (F1,42 = 0.077, p =

0.783). Participants randomized to huperzine or placebo did not differ on measures of

immediate or delayed episodic memory. Specifically, groups did not differ with regard to

performance over three learning trials (F1,42 = 1.262, p = 0.268), nor did they differ on

performance following a 15 minute delay period (F1,42 = 0.449, p = 0.506). Participants

randomized to huperzine or placebo did not differ on measures of working memory as

assessed by the n-back, including mean length of the n-back trials for each block working

memory (F1,42 = 0.005, p = 0.945), maximum block length during each assessment (F1,42 =

36

0.345, p = 0.560), accuracy of responding to auditory stimuli (F1,42 = 2.442, p = 0.126),

and accuracy of responding to visual stimuli (F1,42 = 0.159, p = 0.692).

37

Table 8

Demo/Drug Use Statistics for Study 2

Placebo

(N = 15)

Rivastigmine

(N = 28)

Huperzine

(N = 29)

p

Demographics

Males

Females

13 (87%)

2 (13%)

22 (79%)

6 (21%)

22 (76%)

6 (24%)

Caucasian

African American

4 (27%)

11 (73%)

8 (29%)

20 (71%)

8 (28%)

21 (72%)

Age (years) 39.7±2.0 43.9±1.0 43.2±7.6 .16

Education (years) 12.1±0.3 12.9±0.3 12.7±0.4 .36

IQ (WAIS-III) 96.5±3.8 101.1±1.1 97.0±2.4 .39

Drug Use

Cocaine

Years of use


Grams per day

15.7±1.9

15.8±1.8

1.8±0.3

16.1±1.5

18.6±1.5

2.3±0.5

16.0±1.5

17.6±1.8

2.1±0.3

.98

.72

.60

Cigarette

Years of Use

Cigarettes/day

87% 89% 93%

17.4±2.3

20.2±2.8

21.3±1.7

26.5±1.7

20.66±1.6

26.37±1.5

.37

.07

Alcohol

Years of Use


93% 82% 79%

18.7±2.4

9.9±8.2

20.8±1.5

10.3±1.7

22.3±1.8

10.2±1.9

.42

.99


*p<0.05

38

Table 9

Neurocognitive Performance on those Randomized to Rivastigmine versus Placebo

Placebo

(N = 15)

Rivastigmine

(N = 28)

p

Neurocognitive Performance Post-tx Post-tx

CPT-II Performance

D’ (Sensitivity) 50.23±2.99 49.87±1.58 .91

Hit Rate – RT^ 46.93±3.86 49.26±2.48 .60

Omissions^^ 60.61±5.06 61.61±5.05 .90

HVLT-R Performance

Trials 1-3 31.73±2.13 40.43±1.46 <.001*

Delayed Recall 32.13±2.78 37.29±2.25 .17

N-Back Performance

Auditory Accuracy 0.52±.05 0.62±0.02 .06

Visual Accuracy 0.50±0.05 0.55±0.03 .35

N-value (mean) 1.55±0.11 1.84±0.08 .03

N-value (max) 2.07±0.18 2.61±0.11 .01


^RT=reaction time


*p<0.006

39

Table 10

Neurocognitive Performance on those Randomized to Huperzine versus Placebo

Placebo

(N = 15)

Huperzine

(N = 29)

p

Neurocognitive Performance Post-tx Post-tx

CPT-II Performance

D’ (Sensitivity) 50.23±2.99 51.70±1.61 .64

Hit Rate – RT^ 46.93±3.86 47.90±2.57 .83

Omissions^^ 60.61±5.06 63.95±8.22 .78

HVLT-R Performance

Trials 1-3 31.73±2.13 35.28±1.98 .27

Delayed Recall 32.13±2.78 34.55±2.16 .51

N-Back Performance


Visual Accuracy 0.50±0.05 0.48±0.03 .69

N-value (mean) 1.55±0.11 1.56±0.09 .95

N-value (max) 2.07±0.18 2.21±0.14 .56


^RT=reaction time


**p<0.006

CHAPTER V

CONCLUSION AND SUMMARY

A. Study 1 – Demographic and drug use variables which may affect neurocognition

Overall, as compared to age-matched normative data, the current results indicate

that cocaine users perform at a lower level on neurocognitive assessments. Specifically,

cocaine-dependent participants tended to perform more poorly in the domains of working

memory (since scores on the n-back fell well below the scores of healthy controls

reported by Jaeggi, 2008) and episodic memory (since the t-scores on the HVLT were

well below the normed 43-55 average range). These data demonstrate that

neurocognitive deficits exist in cocaine-dependent individuals irrespective of

demographic, drug use, and behavioral characteristics. Importantly, the current results

coincide with the meta-analysis performed by Jovanovski (2005) which revealed that

cocaine-dependent individuals experienced dysfunction in episodic memory and working

memory.

The data did not reveal gender differences in the domains of attention, working

memory, verbal memory. This finding is of considerable interest since there have been

notable gender differences reported for several neurocognitive domains in the literature in

both healthy controls and cocaine users. Some explanations as to why males and females

performed similarly on neurocognitive tasks warrants discussion. When investigating the

subjective effects of cocaine, males, when compared to females, detected cocaine’s

effects faster and reported more intense positive (e.g. euphoria) and negative (e.g.

dysphoria) subjective responses (Lukas, 1996). In addition, after receiving cocaine in the

laboratory, males who received the same mg/kg dose of cocaine as females, achieved

41

significantly higher plasma cocaine levels when compared to women (Lukas, 1996).

Moreover, females achieve similar cardiovascular increases in heart rate when compared

to males suggesting that females may be more sensitive to the cardiovascular effects of

cocaine when taking into consideration these differences in plasma cocaine levels. It has

previously been reported that elevated levels of progesterone markedly increased the

cardiotoxic effects produced by cocaine (Woods & Plessinger, 1990; Sharma, Plessinger,

Sherer, Liang, Miller, & Woods 1992; Plessinger & Woods, 1990). This may further

explain the impact of hormones on gender differences and stimulant use. While not

directly correlated with neurocognition, gender differences in the behavioral and

cardiovascular responses to cocaine may provide insight into potential mediators into

cocaine’s effect on brain function and neurocognitive performance. However, it must be

noted that the gender differences mentioned above were reported following acute cocaine

administration, which may explain the inconsistency between the findings mentioned in

the literature and our current findings. In our studies, the participants had been abstinent

from cocaine for >3 days, the acute effects of the drug were not present (i.e. the intention

was to determine the effects of long-term, chronic cocaine use rather than evaluating

performance in an intoxicated state). The finding that males and females performed

statistically similar in the cocaine-abstinent condition provides the first evidence that

gender differences do not exist with respect to the long lasting effects of cocaine on

neurocognition. Future studies could assess neurocognition immediately following acute

cocaine administration to determine whether gender differences emerge in that situation.

For example, a recent study by our group demonstrated that acute methamphetamine

exposure improved neurocognition (specifically attention and working memory);

42

however, the sample had an insufficient number of females to conduct a gender analysis

(Mahoney, 2012).

The finding that there were no neurocognitive deficits in cocaine-dependent

individuals who were concurrent cigarette smokers as compared cocaine users alone is

interesting due to the neurocognitive stimulating effects (e.g. improved attention) as well

as deficits produced by nicotine (Mancuso, Lejeune, & Ansseau, 2001). In a recent

review of the literature, cigarette smoking was associated with deficiencies in executive

functioning, cognitive flexibility, general intellectual abilities, learning, episodic

memory, processing speed, and working memory (Durazzo, Meyerhoff, & Nixon, 2010).

Specifically, cigarette smokers exhibit poorer working memory as measured by the n-

back task (similar to the task used in the current study) when compared to non-smokers

(Ernst, Heishman, Spurgeon, & London, 2001, Jacobsen, Krystal, Mend, Westerveld,

Frost, & Pugh, 2005), and perform poorly on tasks focusing on visuospatial working

memory (George et al., 2002). In addition, smokers performed worse than non-smokers

on measure of auditory-verbal memory as measured by assessment such as the Wechsler

Memory Scale (Fried, Watkinson, & Gray, 2006; Cerhan et al., 1998). Conversely, other

studies noted no differences on measures of auditory-verbal learning and memory and

verbal fluency (Kalmijn, van Boxtel, Verschuren, Jolles, & Launer, 2002; Sakurai &

Kanazawa, 2002). Heavy smokers (defined as those who smoked ~40 cigarettes a day)

performed worse than light smokers (defined as those who smoked ~5 cigarettes a day)

on the Wisconsin Card Sorting Task (an assessment of executive functioning (Razani,

Boone, Lesser, & Weiss, 2004). In addition, other reports found that smokers and non-

smokers did not differ on some tasks of executive functioning such as the Trail Making

43

Test B and the Paced Auditory Serial Attention Task (Elwan et al., 1997). Due to the

cognitive deficits produced by cigarette smoking alone (with the exception of the few

studies mentioned), one may assume that comorbid cigarette smoking and cocaine use

may exacerbate cognitive deficiencies; however, the results of this study do not support

this assumption. One potential explanation for this is perhaps that the cocaine use had

caused deficits severe enough that concurrent cigarette smoking caused minimal

additional impairment (the concept of “floor” effects will be discussed later).


individuals who were concurrent alcohol users when compared to those whom were

cocaine-dependent alone is interesting due to the neurocognitive deficits produced by

alcohol. Evidence indicated that chronic (long-term, consistent) alcohol exposure may

result in brain shrinkage which can affect numerous cognitive abilities. For example,

psychomotor speed (the speed at which you are able to physically perform tasks) and

visuospatial abilities (those involving conceptualizing and understanding physical

properties of objects) are both affected by chronic alcohol abuse (Lezak, Howieson, &

Loring, 2004; Parsons & Farr, 1981; Ryan & Butters, 1986). However, other skills, such

as language and arithmetic abilities, are less affected which may lead one to believe that

the chronic alcohol use is not affecting them. In addition, the onset age of alcohol

drinking may account for positive relationships between age/duration and level of

cognitive dysfunction (Pishkin, Lovallo, & Bourne, 1985). Also, it has been reported that

alcohol abuse causes accelerated aging in the brain (Blusewicz, Dustman, Schenkenberg,

& Beck 1977; Graff-Radford, Heaton, Earnest, & Rudikoff, 1982) which in turn causes

impairments of problem-solving skills, memory, and learning (Craik, 1977). While

44

memory may remain intact initially, as the difficulty of tasks increase, performance of

memory functioning gradually declines. It has also been reported that alcohol abuse

leads to deficits in executive functioning. Executive functioning involves several

different aspects of day- to-day life including inhibitory control (being able to stop doing

something inappropriate), initiation (starting a process rather than waiting for someone

else to start it for you), and working memory (holding information in your short-term

memory). In addition, those whom abuse alcohol have problem-solving issues, decreased

flexibility in thinking, as well as problems remembering, which are all related to

executive functioning.

During the detoxification period (which occurs over the 2 weeks following the

stoppage of alcohol use), there are neurocognitive deficits across several cognitive

domains, even those that remain unaffected during active alcohol usage (Ryan,

1986). However, the brain is resilient and has the ability to “bounce back.” So many

cognitive deficits, such as memory and learning abilities, are restored following

abstinence. Memory deficits include problems with declarative memory (long-term

memory where facts and knowledge are stored) and includes anterograde (creating new

memories) and retrograde (remembering old memories) deficits (Butters & Stuss, 1989;

O’Connor & Verfaillie, 2002).

Due to the numerous cognitive deficits produced by alcohol alone, one may

assume that comorbid alcohol and cocaine use may exacerbate or have more of an

additive effect to these cognitive deficiencies; however, the results of this study indicate

that cocaine users alone when compared to concurrent cocaine and alcohol users, do not

differ with respect to neurocognitive functioning. One potential explanation for the

45

groups being statistically similar in the current study is because none of the individuals

included in this study met criteria for alcohol-dependence (the dependence criteria for

alcohol is identical to the criteria for dependence criteria for cocaine mentioned on page

7). Thus, since these individuals were not alcohol-dependent, their regular patterns of

daily alcohol use may not have affected nor caused further decrements in neurocognitive

capabilities. Future studies should investigate the differences between cocaine-

dependent and comorbid cocaine- and alcohol-dependent individuals to further explore

the deficits caused by this comorbidity.


individuals who were concurrent marijuana users when compared to those whom were

cocaine-dependent alone is interesting due to the neurocognitive deficits produced by

marijuana. Marijuana interferes with memory as well as a variety of cognitive processes,

leaving the chronic user less able to adapt, excel, and respond to typical life challenges

(Pope, Gruber, & Yurgelun-Todd, 1996). The cognitive effects produced by marijuana

should be divided into 3 different categories: acute (during marijuana intoxication),

residual (when intoxication wears off, but marijuana is still present in the system), and

chronic (long after marijuana is out of the system) (Solowij, 1999). During the acute

phase, very high doses of marijuana may result in psychotic-like states (Brust, 1993;

Colback & Crowe, 1970). The acute effects of marijuana are noticed in reactive

emotional states including perceptual changes and psychomotor slowing. While several

studies have also reported equivocal results for behavior and cognitive changes following

acute marijuana exposure, there have been reports demonstrating reduced memory

capabilities while under the influence of marijuana (Brust, 2000). However, it has also

46

been reported that, despite subjective report of intoxication, these individuals perform

fairly well on tests of attention while deficits are noted on factual memory and short-term

recall (Iverson, 2000). With regard to the subacute consequences of marijuana use, there

have been reports of decreased performance on tests of attention, memory, and motor

abilities (for review see Pope, Gruber, & Yurgelun-Todd, 1996; Sofuoglu, Sugarman, &

Carroll, 2010). However, in a separate review, when setting stringent criteria including

the inclusion of studies where there was a subacute presence of marijuana and not

intoxication, it was reported that only 55% of individuals demonstrated a level of

cognitive impairment (Gonzalez, Carey, & Grant, 2002). As a result, the long-term

consequences (residual effects) of marijuana usage is not quite clear. The literature has

demonstrated that learning and reaction time tests in marijuana users and controls

demonstrated no differences (Lezak et al., 2004). While there appear to be no significant

long-term cognitive deficits in marijuana users, there are noted personality changes. For

example, it has been reported that marijuana users express apathy (a general “not

caring”), restlessness, and sluggishness (Brust, 1993; Carlin & O’Malley, 1996). These

characteristics lead to lessened motivation, poor relationships, and not being able to

perform tasks as usual. It must be noted though that these reports have been subjected to

great debate since several other studies have found no long-term deficits (Lezak et al.,

2004). The reduced memory capabilities may be a result of poor attention. Also, since

marijuana is frequently used with alcohol, there may be additive effects which may lead

to impaired functioning and may contribute to poor decision making resulting in unsafe

behaviors (e.g. driving under the influence).

47

Due to all of the cognitive deficits produced by marijuana alone, one may assume

that comorbid marijuana and cocaine use may exacerbate cognitive deficiencies;

however, the results indicate that cocaine users alone when compared to concurrent

cocaine and marijuana users, do not differ with respect to neurocognitive functioning.

One potential explanation for the groups being statistically similar is that none of the

individuals included in this study met criteria for marijuana-dependence (the dependence

criteria for marijuana is identical to the criteria for dependence criteria for cocaine

mentioned on page 7). . Thus, since these individuals were not marijuana-dependent,

their casual use of marijuana appears to not affect neurocognition. Future studies could

investigate the differences between cocaine-dependent and comorbid cocaine- and

marijuana-dependent individuals.

Despite the detailed and informative outcomes presented in the studies conducted,

some methodological limitations should be noted. First of all, the sample sizes are

relatively small and much larger sample sizes should be obtained before making

conclusive statements as to whether gender, ethnic, or comorbid drug use differences

exist in cocaine users. Secondly, since this neurocognitive battery only focused on

working memory, attention, and verbal learning and memory, a more comprehensive

battery may demonstrate differences in other domains. In addition, the study would have

been strengthened by including a comparison of a non-drug using, healthy control group

to determine exactly how prevalent the neurocognitive deficits are in cocaine-dependent

individuals (rather than relying on the age-matched normative values as a comparison).

Notwithstanding, the current results demonstrate that gender, ethnic, or comorbid drug

48

use differences in neurocognitive performance in cocaine-dependent participants may not

be prevalent.

Although there were no strong correlations between demographic and drug use

variables and neurocognition, there were some interesting findings by on the significance

values. For example, when comparing the oldest and youngest participants, younger

participants performed significantly better on 2 separate indices of working memory.

This supports the notion that prefrontal cortex functioning worsens over time. In addition,

there were no differences between those with the highest education versus those with the

lowest education. This is a critical finding because it demonstrates that level of education

(or years of formal learning) did not affect neurocognitive processes. Interestingly,

however, participants with the highest IQ’s performed significantly better when

compared to those with the lowest IQ’s across several domains including episodic

memory (both immediate and delayed) and working memory. These data support the

rationale for matching groups (involved in the gender, ethnic, and comorbid substance

use comparisons) on IQ in addition to the other demographic variables (e.g. age,

education, drug use variables, etc.). Moreover, this finding may demonstrate that IQ may

be protective against deficits caused by cocaine use in the domains of verbal and working

memory.

It has previously been reported that cocaine induced neurocognitive deficits are

correlated with the severity of cocaine use, suggesting a dose related effect (Bolla,

Rothman, and Cadet, 1999). Our findings indicate that individuals who used cocaine for

more years and for more days in the past 30 did not differ from those individuals that

used for the fewest years and the fewest days in the past 30. However, those individuals

49

who used more grams per day had significantly higher auditory accuracy (a measure of

working memory) when compared to those reporting using fewer grams per day. It may

be logically hypothesized that more years of use, recent use, and grams per day would

lead to further cognitive impairment which makes this finding especially interesting. One

potential explanation for this unexpected finding is that once a certain threshold is met,

further impairment does not occur. In other words, if an individual uses cocaine for a

certain number of years, it appears that the neurocognitive damage is done and further

years of use do not exacerbate those deficits. Similarly, if an individual uses for a certain

number of days per month or uses a certain amount of cocaine per day, those

neurocognitive deficits occur and remain at a consistent “steady state”, so that additional

use does not cause further impairment. This is speculation, however, and would need to

be evaluated in future studies.

With regard to the behavioral questionnaires (BDI-II, LSC-R, and the ASI-LITE),

there were no differences in neurocognition between those who scored the highest (e.g.

endorsed the most symptoms) versus those who scored the lowest (e.g. endorsed the

fewest symptoms) indicating that these behavioral variables may not affect

neurocognition. Memory deficits caused by clinical depression is a common occurrence

and has been termed “pseudodementia” (Patterson, 1986; Wells, 1979) which may lead to

speculation that increased BDI-II scores (endorsing more depressive symptoms) may

result in deficits in episodic or working memory; however, this was not found in the

current study. One possible explanation for this finding is that none of the individuals

had an Axis I psychiatric diagnosis of depression (rather they simply endorsed depressive

symptoms without meeting actual diagnostic criteria. Factors related to and potentially

50

affecting BDI-II symptomatology include lifetime stress and addiction severity. Previous

research has found that individuals with higher lifetime stress have significantly higher

BDI-II scores as well as addiction severity (Mahoney, Newton, Omar, Ross, & De La

Garza, 2012). In addition, chronic stress leads to deficits in declarative memory

(McEwen, 2004). In addition, higher ASI-LITE scores indicate elevated levels of

psychosocial dysfunction which may result in higher reported stress. However, in the

current study, those individuals with higher LSC-R scores and ASI-LITE scores did not

endorse more neurocognitive deficits. One potential explanation for these findings is that

their cocaine usage resulted in neurocognitive deficits, but they were not further affected

by stress nor addiction severity.

B. Study 2 – Rivastigmine or Huperzine as a treatment for neurocognitive impairment

The findings from this study demonstrated that while there was no effect of

rivastigmine on sustained attention, rivastigmine administration did significantly improve

episodic memory (as measured by increased immediate recall on the HVLT) and

working memory (by increased values on both the mean and max block length on the n-

back assessment). Since rivastigmine has previously been shown to reduce the positive

subjective effects (e.g. desire and likely to use) produced by the stimulant

methamphetamine, the cognitive enhancing effects of rivastigmine found in this

population of cocaine-dependent individuals is critical. A current trend in the

development of pharmacotherapies for cocaine-dependence involves the utilization of

combination medications (more than one medication that have different brain or

neurochemical targets to combat the various effects produced by cocaine use). Thus, one

solution would be to pair a cognitive enhancing agent with another medication that

51

decreases the reinforcing or positive effects produced by cocaine in an attempt to

maximize the potential benefit and outcomes. However, rivastigmine alone may

accomplish both of these tasks – by improving neurocognition and reducing the positive

subjective effects associated with cocaine usage. This is of great importance because

isolating a single efficacious compound may result in fewer side effects, less time

titrating to the most effective dose since there is only one medication being utilized, and

also eliminate the potential for adverse medication-medication interactions. Furthermore,

the results of this study are especially interesting given the fact that the same doses of

rivastigmine (3 and 6 mg) for a similar duration (6 days) showed no effect on

neurocognition in methamphetamine-dependent individuals (Kalechstein, 2011). This

demonstrates that the neurocognitive deficits produced by cocaine use may be more

easily treated by rivastigmine when compared to those deficits produced by

methamphetamine.

It is important to concede some limitations with this study that may have affected

the outcomes. Specifically, rivastigmine administration was most likely to be associated

with improved neurocognitive function in studies that utilized higher doses, e.g., up to 12

mg per day for much longer period of times, e.g., 39 weeks (Silver et al., 2009); for this

study, the maximum dose was 6 mg for a period of 8 days. It is plausible that this aspect

of the study design mitigated the efficacy of rivastigmine, especially on the domain of

attention where no effect was demonstrated as well as other domains of neurocognitive

functioning which were not evaluated.

There were no changes in neurocognition with respect to the domains of attention,

episodic memory, or working memory following huperzine administration. Since there is

52

no published literature on the effects of huperzine on neurocognition in cocaine-

dependent individuals, speculation as to why huperzine did not improve cognition in this

population warrants further discussion. Huperzine administration was most likely to be

associated with improved neurocognitive function in studies that utilized a longer

duration of treatment, e.g., 12 weeks (Xu, Liang, Juan-Wu, Zhang, Zhu, & Jiang2012),

whereas in this study, the maximum dose was 0.8 mg for a period of 8 days. It is

plausible that this aspect of the study design mitigated the efficacy of huperzine across all

domains. Because huperzine is characterized as a cognition enhancing agent that

modulates the acetylcholine system, it seemed reasonable to study whether low-dose,

short-term huperzine administration might remedy, at least in part, cocaine associated

neurocognitive impairment. Another explanation is that participants were exposed to

low-dose cocaine (40 mg) during the study; nonetheless, it probably was not a confound

given that exposure was identical for each study arm with regard to the amount and

timing of the cocaine dose.

C. Overall Conclusion and Summary

Respective of these outcomes from Study 1 and Study 2, we contend that cocaine

associated neurocognitive impairment remains an important target of treatment. This

perception is consistent with that of other leading researchers in the field, particularly

given the prevalence of cocaine associated neurocognitive impairment and the fact that

the condition does not resolve with protracted abstinence (Sofuoglu, 2010). Furthermore,

the association between neurocognitive impairment and functional outcomes, such as

employment status for participants diagnosed with other disorders, e.g., traumatic brain

injury, epilepsy, and HIV, is well-documented (Kalechstein, Newton, & van Gorp, 2003).

53

Given that cocaine addiction is associated with widespread functional difficulties, such as

unemployment and relapse to dependence, it is plausible that reversing neurocognitive

impairments associated with this disease will concurrently ameliorate these functional

difficulties as well.

Future studies might also examine the degree to which improved neurocognition

influences day-to-day functioning in long-term, high-dose cocaine users. While

laboratory-based studies, such as those conducted above, provide potentially important

information regarding the possibility of remediating cocaine-associated neurocognitive

impairment, the ultimate determination of medication efficacy will be whether

administration of a medication will confer some sort of benefit in terms of important

daily activities. For example, such individuals are often required to complete treatment

for the initiation and maintenance of abstinence from cocaine. Moreover, previous

studies have revealed an associated between poor working memory function and

increased likelihood of dropout from treatment (Jovanovski et al., 2005). Thus, a future

study might examine whether administration of rivastigmine concurrently improves

performance on episodic and working memory tasks and treatment outcome.

54

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